Overview

Dataset statistics

Number of variables56
Number of observations15120
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.5 MiB
Average record size in memory448.0 B

Variable types

BOOL44
NUM12

Reproduction

Analysis started2022-05-11 12:39:30.222270
Analysis finished2022-05-11 12:40:12.297750
Duration42.08 seconds
Versionpandas-profiling v2.8.0
Command linepandas_profiling --config_file config.yaml [YOUR_FILE.csv]
Download configurationconfig.yaml

Warnings

Soil_Type7 has constant value "0" Constant
Soil_Type15 has constant value "0" Constant
Id has unique values Unique
Horizontal_Distance_To_Hydrology has 1590 (10.5%) zeros Zeros
Vertical_Distance_To_Hydrology has 1890 (12.5%) zeros Zeros

Variables

Id
Real number (ℝ≥0)

UNIQUE

Distinct count15120
Unique (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7560.5
Minimum1
Maximum15120
Zeros0
Zeros (%)0.0%
Memory size118.1 KiB
2022-05-11T15:40:12.501299image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile756.95
Q13780.75
median7560.5
Q311340.25
95-th percentile14364.05
Maximum15120
Range15119
Interquartile range (IQR)7559.5

Descriptive statistics

Standard deviation4364.91237
Coefficient of variation (CV)0.5773311779
Kurtosis-1.2
Mean7560.5
Median Absolute Deviation (MAD)3780
Skewness0
Sum114314760
Variance19052460
2022-05-11T15:40:12.657748image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
11< 0.1%
 
100861< 0.1%
 
100741< 0.1%
 
100751< 0.1%
 
100761< 0.1%
 
100771< 0.1%
 
100781< 0.1%
 
100791< 0.1%
 
100801< 0.1%
 
100811< 0.1%
 
Other values (15110)1511099.9%
 
ValueCountFrequency (%) 
11< 0.1%
 
21< 0.1%
 
31< 0.1%
 
41< 0.1%
 
51< 0.1%
 
ValueCountFrequency (%) 
151201< 0.1%
 
151191< 0.1%
 
151181< 0.1%
 
151171< 0.1%
 
151161< 0.1%
 

Elevation
Real number (ℝ≥0)

Distinct count1665
Unique (%)11.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2749.3225529100528
Minimum1863
Maximum3849
Zeros0
Zeros (%)0.0%
Memory size118.1 KiB
2022-05-11T15:40:12.800406image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum1863
5-th percentile2117
Q12376
median2752
Q33104
95-th percentile3397
Maximum3849
Range1986
Interquartile range (IQR)728

Descriptive statistics

Standard deviation417.6781873
Coefficient of variation (CV)0.151920402
Kurtosis-1.082115791
Mean2749.322553
Median Absolute Deviation (MAD)367
Skewness0.07563970694
Sum41569757
Variance174455.0682
2022-05-11T15:40:13.071357image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
2830250.2%
 
2290250.2%
 
3371240.2%
 
2952230.2%
 
2955230.2%
 
2820230.2%
 
3244230.2%
 
2795230.2%
 
2850220.1%
 
2962220.1%
 
Other values (1655)1488798.5%
 
ValueCountFrequency (%) 
18631< 0.1%
 
18741< 0.1%
 
18791< 0.1%
 
18881< 0.1%
 
18892< 0.1%
 
ValueCountFrequency (%) 
38492< 0.1%
 
38481< 0.1%
 
38462< 0.1%
 
38441< 0.1%
 
38421< 0.1%
 

Aspect
Real number (ℝ≥0)

Distinct count361
Unique (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean156.67665343915343
Minimum0
Maximum360
Zeros110
Zeros (%)0.7%
Memory size118.1 KiB
2022-05-11T15:40:13.211565image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile13
Q165
median126
Q3261
95-th percentile344
Maximum360
Range360
Interquartile range (IQR)196

Descriptive statistics

Standard deviation110.0858014
Coefficient of variation (CV)0.7026305386
Kurtosis-1.150244484
Mean156.6766534
Median Absolute Deviation (MAD)77
Skewness0.450935294
Sum2368951
Variance12118.88367
2022-05-11T15:40:13.348806image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
451170.8%
 
01100.7%
 
901090.7%
 
63890.6%
 
76870.6%
 
27820.5%
 
315810.5%
 
75800.5%
 
108790.5%
 
117780.5%
 
Other values (351)1420894.0%
 
ValueCountFrequency (%) 
01100.7%
 
1480.3%
 
2500.3%
 
3540.4%
 
4510.3%
 
ValueCountFrequency (%) 
3602< 0.1%
 
359330.2%
 
358470.3%
 
357580.4%
 
356500.3%
 

Slope
Real number (ℝ≥0)

Distinct count52
Unique (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.501587301587303
Minimum0
Maximum52
Zeros5
Zeros (%)< 0.1%
Memory size118.1 KiB
2022-05-11T15:40:13.494105image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5
Q110
median15
Q322
95-th percentile32
Maximum52
Range52
Interquartile range (IQR)12

Descriptive statistics

Standard deviation8.453926762
Coefficient of variation (CV)0.5123099134
Kurtosis-0.2383101358
Mean16.5015873
Median Absolute Deviation (MAD)6
Skewness0.5236583383
Sum249504
Variance71.4688777
2022-05-11T15:40:13.623339image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
117404.9%
 
107394.9%
 
137174.7%
 
146994.6%
 
126774.5%
 
156644.4%
 
96644.4%
 
166404.2%
 
175984.0%
 
85743.8%
 
Other values (42)840855.6%
 
ValueCountFrequency (%) 
05< 0.1%
 
1780.5%
 
21340.9%
 
32101.4%
 
43052.0%
 
ValueCountFrequency (%) 
521< 0.1%
 
501< 0.1%
 
495< 0.1%
 
481< 0.1%
 
473< 0.1%
 

Horizontal_Distance_To_Hydrology
Real number (ℝ≥0)

ZEROS

Distinct count400
Unique (%)2.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean227.19570105820105
Minimum0
Maximum1343
Zeros1590
Zeros (%)10.5%
Memory size118.1 KiB
2022-05-11T15:40:13.763752image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q167
median180
Q3330
95-th percentile631
Maximum1343
Range1343
Interquartile range (IQR)263

Descriptive statistics

Standard deviation210.0752957
Coefficient of variation (CV)0.9246446774
Kurtosis2.803984388
Mean227.1957011
Median Absolute Deviation (MAD)120
Skewness1.488052491
Sum3435199
Variance44131.62986
2022-05-11T15:40:13.893431image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
0159010.5%
 
3012078.0%
 
1504973.3%
 
604903.2%
 
424523.0%
 
674112.7%
 
853812.5%
 
1083612.4%
 
902841.9%
 
1202831.9%
 
Other values (390)916460.6%
 
ValueCountFrequency (%) 
0159010.5%
 
3012078.0%
 
424523.0%
 
604903.2%
 
674112.7%
 
ValueCountFrequency (%) 
13431< 0.1%
 
13181< 0.1%
 
12941< 0.1%
 
12612< 0.1%
 
12602< 0.1%
 

Vertical_Distance_To_Hydrology
Real number (ℝ)

ZEROS

Distinct count423
Unique (%)2.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51.076521164021166
Minimum-146
Maximum554
Zeros1890
Zeros (%)12.5%
Memory size118.1 KiB
2022-05-11T15:40:14.033507image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum-146
5-th percentile-4
Q15
median32
Q379
95-th percentile176
Maximum554
Range700
Interquartile range (IQR)74

Descriptive statistics

Standard deviation61.23940613
Coefficient of variation (CV)1.198973711
Kurtosis3.403498704
Mean51.07652116
Median Absolute Deviation (MAD)32
Skewness1.53777568
Sum772277
Variance3750.264863
2022-05-11T15:40:14.162124image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
0189012.5%
 
52171.4%
 
32061.4%
 
42001.3%
 
81981.3%
 
71821.2%
 
101761.2%
 
91661.1%
 
21651.1%
 
61621.1%
 
Other values (413)1155876.4%
 
ValueCountFrequency (%) 
-1461< 0.1%
 
-1341< 0.1%
 
-1231< 0.1%
 
-1151< 0.1%
 
-1141< 0.1%
 
ValueCountFrequency (%) 
5541< 0.1%
 
5472< 0.1%
 
4111< 0.1%
 
4031< 0.1%
 
4011< 0.1%
 

Horizontal_Distance_To_Roadways
Real number (ℝ≥0)

Distinct count3250
Unique (%)21.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1714.0232142857142
Minimum0
Maximum6890
Zeros3
Zeros (%)< 0.1%
Memory size118.1 KiB
2022-05-11T15:40:14.311386image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile242
Q1764
median1316
Q32270
95-th percentile4635.1
Maximum6890
Range6890
Interquartile range (IQR)1506

Descriptive statistics

Standard deviation1325.066358
Coefficient of variation (CV)0.7730737525
Kurtosis1.022419366
Mean1714.023214
Median Absolute Deviation (MAD)690
Skewness1.247810678
Sum25916031
Variance1755800.854
2022-05-11T15:40:14.446216image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
150880.6%
 
120560.4%
 
390470.3%
 
618450.3%
 
1110430.3%
 
700410.3%
 
108380.3%
 
900370.2%
 
1273370.2%
 
990370.2%
 
Other values (3240)1465196.9%
 
ValueCountFrequency (%) 
03< 0.1%
 
30150.1%
 
425< 0.1%
 
60110.1%
 
67130.1%
 
ValueCountFrequency (%) 
68901< 0.1%
 
68361< 0.1%
 
68111< 0.1%
 
67661< 0.1%
 
66791< 0.1%
 

Hillshade_9am
Real number (ℝ≥0)

Distinct count176
Unique (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean212.70429894179895
Minimum0
Maximum254
Zeros1
Zeros (%)< 0.1%
Memory size118.1 KiB
2022-05-11T15:40:14.584852image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile151
Q1196
median220
Q3235
95-th percentile250
Maximum254
Range254
Interquartile range (IQR)39

Descriptive statistics

Standard deviation30.56128689
Coefficient of variation (CV)0.143679686
Kurtosis1.218810484
Mean212.7042989
Median Absolute Deviation (MAD)18
Skewness-1.093680561
Sum3216089
Variance933.9922561
2022-05-11T15:40:14.718668image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
2262791.8%
 
2292691.8%
 
2242651.8%
 
2282611.7%
 
2302601.7%
 
2332481.6%
 
2232451.6%
 
2192421.6%
 
2312391.6%
 
2252361.6%
 
Other values (166)1257683.2%
 
ValueCountFrequency (%) 
01< 0.1%
 
581< 0.1%
 
592< 0.1%
 
651< 0.1%
 
731< 0.1%
 
ValueCountFrequency (%) 
2541901.3%
 
2532001.3%
 
2521891.2%
 
2511741.2%
 
2501921.3%
 

Hillshade_Noon
Real number (ℝ≥0)

Distinct count141
Unique (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean218.96560846560845
Minimum99
Maximum254
Zeros0
Zeros (%)0.0%
Memory size118.1 KiB
2022-05-11T15:40:14.848296image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum99
5-th percentile175
Q1207
median223
Q3235
95-th percentile250
Maximum254
Range155
Interquartile range (IQR)28

Descriptive statistics

Standard deviation22.80196554
Coefficient of variation (CV)0.1041349174
Kurtosis1.153484179
Mean218.9656085
Median Absolute Deviation (MAD)14
Skewness-0.9532317075
Sum3310760
Variance519.9296327
2022-05-11T15:40:14.986521image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
2253272.2%
 
2293242.1%
 
2263202.1%
 
2243132.1%
 
2303112.1%
 
2233032.0%
 
2322982.0%
 
2222972.0%
 
2282941.9%
 
2182931.9%
 
Other values (131)1204079.6%
 
ValueCountFrequency (%) 
994< 0.1%
 
1021< 0.1%
 
1031< 0.1%
 
1071< 0.1%
 
1112< 0.1%
 
ValueCountFrequency (%) 
2541330.9%
 
2531631.1%
 
2521521.0%
 
2511831.2%
 
2501671.1%
 

Hillshade_3pm
Real number (ℝ≥0)

Distinct count247
Unique (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean135.09199735449735
Minimum0
Maximum248
Zeros88
Zeros (%)0.6%
Memory size118.1 KiB
2022-05-11T15:40:15.134333image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile53
Q1106
median138
Q3167
95-th percentile207
Maximum248
Range248
Interquartile range (IQR)61

Descriptive statistics

Standard deviation45.89518871
Coefficient of variation (CV)0.3397328458
Kurtosis-0.08734390755
Mean135.0919974
Median Absolute Deviation (MAD)30
Skewness-0.3408272326
Sum2042591
Variance2106.368347
2022-05-11T15:40:15.265862image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
1431821.2%
 
1491611.1%
 
1321561.0%
 
1331541.0%
 
1421541.0%
 
1361541.0%
 
1371521.0%
 
1381481.0%
 
1541481.0%
 
1521451.0%
 
Other values (237)1356689.7%
 
ValueCountFrequency (%) 
0880.6%
 
11< 0.1%
 
33< 0.1%
 
41< 0.1%
 
62< 0.1%
 
ValueCountFrequency (%) 
2482< 0.1%
 
2474< 0.1%
 
2464< 0.1%
 
2454< 0.1%
 
2443< 0.1%
 
Distinct count2710
Unique (%)17.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1511.1472883597883
Minimum0
Maximum6993
Zeros2
Zeros (%)< 0.1%
Memory size118.1 KiB
2022-05-11T15:40:15.398388image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile296.9
Q1730
median1256
Q31988.25
95-th percentile3663.05
Maximum6993
Range6993
Interquartile range (IQR)1258.25

Descriptive statistics

Standard deviation1099.936493
Coefficient of variation (CV)0.7278817235
Kurtosis3.385415788
Mean1511.147288
Median Absolute Deviation (MAD)595
Skewness1.617098874
Sum22848547
Variance1209860.288
2022-05-11T15:40:15.530954image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
618650.4%
 
541510.3%
 
636450.3%
 
607430.3%
 
960420.3%
 
573420.3%
 
752410.3%
 
942400.3%
 
242400.3%
 
342400.3%
 
Other values (2700)1467197.0%
 
ValueCountFrequency (%) 
02< 0.1%
 
3090.1%
 
42110.1%
 
60100.1%
 
67200.1%
 
ValueCountFrequency (%) 
69931< 0.1%
 
68531< 0.1%
 
67231< 0.1%
 
66861< 0.1%
 
66611< 0.1%
 
Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.1 KiB
0
11523
1
3597
ValueCountFrequency (%) 
01152376.2%
 
1359723.8%
 
Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.1 KiB
0
14621
1
 
499
ValueCountFrequency (%) 
01462196.7%
 
14993.3%
 
Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.1 KiB
0
8771
1
6349
ValueCountFrequency (%) 
0877158.0%
 
1634942.0%
 
Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.1 KiB
0
10445
1
4675
ValueCountFrequency (%) 
01044569.1%
 
1467530.9%
 

Soil_Type1
Boolean

Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.1 KiB
0
14765
1
 
355
ValueCountFrequency (%) 
01476597.7%
 
13552.3%
 

Soil_Type2
Boolean

Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.1 KiB
0
14497
1
 
623
ValueCountFrequency (%) 
01449795.9%
 
16234.1%
 

Soil_Type3
Boolean

Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.1 KiB
0
14158
1
 
962
ValueCountFrequency (%) 
01415893.6%
 
19626.4%
 

Soil_Type4
Boolean

Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.1 KiB
0
14277
1
 
843
ValueCountFrequency (%) 
01427794.4%
 
18435.6%
 

Soil_Type5
Boolean

Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.1 KiB
0
14955
1
 
165
ValueCountFrequency (%) 
01495598.9%
 
11651.1%
 

Soil_Type6
Boolean

Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.1 KiB
0
14470
1
 
650
ValueCountFrequency (%) 
01447095.7%
 
16504.3%
 

Soil_Type7
Boolean

CONSTANT
REJECTED

Distinct count1
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.1 KiB
0
15120
ValueCountFrequency (%) 
015120100.0%
 

Soil_Type8
Boolean

Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.1 KiB
0
15119
1
 
1
ValueCountFrequency (%) 
015119> 99.9%
 
11< 0.1%
 

Soil_Type9
Boolean

Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.1 KiB
0
15110
1
 
10
ValueCountFrequency (%) 
01511099.9%
 
1100.1%
 
Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.1 KiB
0
12978
1
 
2142
ValueCountFrequency (%) 
01297885.8%
 
1214214.2%
 
Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.1 KiB
0
14714
1
 
406
ValueCountFrequency (%) 
01471497.3%
 
14062.7%
 
Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.1 KiB
0
14893
1
 
227
ValueCountFrequency (%) 
01489398.5%
 
12271.5%
 
Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.1 KiB
0
14644
1
 
476
ValueCountFrequency (%) 
01464496.9%
 
14763.1%
 
Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.1 KiB
0
14951
1
 
169
ValueCountFrequency (%) 
01495198.9%
 
11691.1%
 

Soil_Type15
Boolean

CONSTANT
REJECTED

Distinct count1
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.1 KiB
0
15120
ValueCountFrequency (%) 
015120100.0%
 
Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.1 KiB
0
15006
1
 
114
ValueCountFrequency (%) 
01500699.2%
 
11140.8%
 
Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.1 KiB
0
14508
1
 
612
ValueCountFrequency (%) 
01450896.0%
 
16124.0%
 
Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.1 KiB
0
15060
1
 
60
ValueCountFrequency (%) 
01506099.6%
 
1600.4%
 
Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.1 KiB
0
15074
1
 
46
ValueCountFrequency (%) 
01507499.7%
 
1460.3%
 
Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.1 KiB
0
14981
1
 
139
ValueCountFrequency (%) 
01498199.1%
 
11390.9%
 
Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.1 KiB
0
15104
1
 
16
ValueCountFrequency (%) 
01510499.9%
 
1160.1%
 
Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.1 KiB
0
14775
1
 
345
ValueCountFrequency (%) 
01477597.7%
 
13452.3%
 
Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.1 KiB
0
14363
1
 
757
ValueCountFrequency (%) 
01436395.0%
 
17575.0%
 
Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.1 KiB
0
14863
1
 
257
ValueCountFrequency (%) 
01486398.3%
 
12571.7%
 
Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.1 KiB
0
15119
1
 
1
ValueCountFrequency (%) 
015119> 99.9%
 
11< 0.1%
 
Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.1 KiB
0
15066
1
 
54
ValueCountFrequency (%) 
01506699.6%
 
1540.4%
 
Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.1 KiB
0
15105
1
 
15
ValueCountFrequency (%) 
01510599.9%
 
1150.1%
 
Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.1 KiB
0
15111
1
 
9
ValueCountFrequency (%) 
01511199.9%
 
190.1%
 
Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.1 KiB
0
13829
1
 
1291
ValueCountFrequency (%) 
01382991.5%
 
112918.5%
 
Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.1 KiB
0
14395
1
 
725
ValueCountFrequency (%) 
01439595.2%
 
17254.8%
 
Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.1 KiB
0
14788
1
 
332
ValueCountFrequency (%) 
01478897.8%
 
13322.2%
 
Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.1 KiB
0
14430
1
 
690
ValueCountFrequency (%) 
01443095.4%
 
16904.6%
 
Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.1 KiB
0
14504
1
 
616
ValueCountFrequency (%) 
01450495.9%
 
16164.1%
 
Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.1 KiB
0
15098
1
 
22
ValueCountFrequency (%) 
01509899.9%
 
1220.1%
 
Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.1 KiB
0
15018
1
 
102
ValueCountFrequency (%) 
01501899.3%
 
11020.7%
 
Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.1 KiB
0
15110
1
 
10
ValueCountFrequency (%) 
01511099.9%
 
1100.1%
 
Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.1 KiB
0
15086
1
 
34
ValueCountFrequency (%) 
01508699.8%
 
1340.2%
 
Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.1 KiB
0
14392
1
 
728
ValueCountFrequency (%) 
01439295.2%
 
17284.8%
 
Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.1 KiB
0
14463
1
 
657
ValueCountFrequency (%) 
01446395.7%
 
16574.3%
 
Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.1 KiB
0
14661
1
 
459
ValueCountFrequency (%) 
01466197.0%
 
14593.0%
 

Cover_Type
Real number (ℝ≥0)

Distinct count7
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.0
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size118.1 KiB
2022-05-11T15:40:15.700800image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q36
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.000066141
Coefficient of variation (CV)0.5000165352
Kurtosis-1.250016528
Mean4
Median Absolute Deviation (MAD)2
Skewness0
Sum60480
Variance4.000264568
2022-05-11T15:40:15.831142image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
5216014.3%
 
2216014.3%
 
1216014.3%
 
7216014.3%
 
3216014.3%
 
6216014.3%
 
4216014.3%
 
ValueCountFrequency (%) 
1216014.3%
 
2216014.3%
 
3216014.3%
 
4216014.3%
 
5216014.3%
 
ValueCountFrequency (%) 
7216014.3%
 
6216014.3%
 
5216014.3%
 
4216014.3%
 
3216014.3%
 

Interactions

2022-05-11T15:39:41.312440image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:41.507361image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:41.690433image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:41.862975image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:42.030156image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:42.312947image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:42.486548image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:42.663337image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:42.830369image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:43.009570image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:43.185548image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:43.362130image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:43.531956image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:43.705482image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:43.880104image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:44.052517image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:44.220482image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:44.399175image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:44.574685image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:44.753105image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:44.921957image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:45.101544image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:45.272393image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:45.451196image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:45.623226image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:45.794930image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:45.969129image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:46.140199image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:46.307643image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:46.484209image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:46.802225image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:46.978294image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:47.146545image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:47.321862image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:47.489013image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:47.664466image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:47.834966image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:48.000591image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:48.164360image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:48.326920image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:48.487093image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:48.653889image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:48.817380image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:48.984367image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:49.142447image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:49.309317image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:49.469585image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:49.635651image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:49.794761image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:49.971545image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:50.148769image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:50.329358image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:50.498986image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:50.676932image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:50.851124image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:51.189444image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:51.368532image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:51.684328image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:52.005728image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:52.273860image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:52.466515image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:52.673408image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:52.873708image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:53.064273image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:53.259554image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:53.470790image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:53.674880image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:53.881788image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:54.054709image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:54.240348image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:54.430595image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:54.646512image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:54.824094image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:55.009527image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:55.197335image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:55.384986image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:55.564085image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:55.742998image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:55.918706image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:56.097030image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:56.418681image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:56.599525image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:56.772998image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:56.952282image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:57.124389image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:57.289109image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:57.455899image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:57.618845image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:57.774845image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:57.941435image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:58.107804image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:58.274995image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:58.432961image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:58.599243image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:58.756331image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:58.930494image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:59.090468image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:59.268795image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:59.451882image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:59.631420image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:59.806491image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:39:59.993129image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:40:00.191583image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:40:00.377625image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:40:00.557135image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:40:00.892063image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:40:01.087869image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:40:01.274612image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:40:01.493353image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:40:01.660778image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:40:01.830066image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:40:01.999982image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:40:02.160336image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:40:02.331223image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:40:02.499602image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:40:02.669378image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:40:02.829509image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:40:03.001873image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:40:03.166504image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:40:03.337940image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:40:03.501799image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:40:03.678569image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:40:03.854228image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:40:04.028430image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:40:04.198279image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:40:04.379742image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:40:04.564869image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:40:04.748353image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:40:04.922469image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:40:05.104830image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:40:05.426820image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:40:05.604738image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:40:05.779591image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:40:05.947915image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:40:06.122330image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:40:06.295906image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:40:06.459868image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:40:06.634366image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:40:06.819255image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:40:06.996689image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:40:07.164676image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:40:07.338764image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:40:07.502268image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:40:07.675127image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Correlations

2022-05-11T15:40:16.076466image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-05-11T15:40:17.476078image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-05-11T15:40:18.729589image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-05-11T15:40:20.076910image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-05-11T15:40:08.108676image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-11T15:40:11.296389image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Sample

First rows

IdElevationAspectSlopeHorizontal_Distance_To_HydrologyVertical_Distance_To_HydrologyHorizontal_Distance_To_RoadwaysHillshade_9amHillshade_NoonHillshade_3pmHorizontal_Distance_To_Fire_PointsWilderness_Area1Wilderness_Area2Wilderness_Area3Wilderness_Area4Soil_Type1Soil_Type2Soil_Type3Soil_Type4Soil_Type5Soil_Type6Soil_Type7Soil_Type8Soil_Type9Soil_Type10Soil_Type11Soil_Type12Soil_Type13Soil_Type14Soil_Type15Soil_Type16Soil_Type17Soil_Type18Soil_Type19Soil_Type20Soil_Type21Soil_Type22Soil_Type23Soil_Type24Soil_Type25Soil_Type26Soil_Type27Soil_Type28Soil_Type29Soil_Type30Soil_Type31Soil_Type32Soil_Type33Soil_Type34Soil_Type35Soil_Type36Soil_Type37Soil_Type38Soil_Type39Soil_Type40Cover_Type
01259651325805102212321486279100000000000000000000000000000001000000000005
122590562212-63902202351516225100000000000000000000000000000001000000000005
23280413992686531802342381356121100000000000000100000000000000000000000000002
3427851551824211830902382381226211100000000000000000000000000000000100000000002
452595452153-13912202341506172100000000000000000000000000000001000000000005
5625791326300-15672302371406031100000000000000000000000000000001000000000002
67260645727056332222251386256100000000000000000000000000000001000000000005
78260549423475732222301446228100000000000000000000000000000001000000000005
892617459240566662232211336244100000000000000000000000000000001000000000005
91026125910247116362282191246230100000000000000000000000000000001000000000005

Last rows

IdElevationAspectSlopeHorizontal_Distance_To_HydrologyVertical_Distance_To_HydrologyHorizontal_Distance_To_RoadwaysHillshade_9amHillshade_NoonHillshade_3pmHorizontal_Distance_To_Fire_PointsWilderness_Area1Wilderness_Area2Wilderness_Area3Wilderness_Area4Soil_Type1Soil_Type2Soil_Type3Soil_Type4Soil_Type5Soil_Type6Soil_Type7Soil_Type8Soil_Type9Soil_Type10Soil_Type11Soil_Type12Soil_Type13Soil_Type14Soil_Type15Soil_Type16Soil_Type17Soil_Type18Soil_Type19Soil_Type20Soil_Type21Soil_Type22Soil_Type23Soil_Type24Soil_Type25Soil_Type26Soil_Type27Soil_Type28Soil_Type29Soil_Type30Soil_Type31Soil_Type32Soil_Type33Soil_Type34Soil_Type35Soil_Type36Soil_Type37Soil_Type38Soil_Type39Soil_Type40Cover_Type
151101511125083326671644204173911385001000000000010000000000000000000000000000006
1511115112261059176010674231202981328001000000000010000000000000000000000000000006
1511215113260038251240589212178891261001000000000010000000000000000000000000000006
151131511426881041544310805245219991266001000000000001000000000000000000000000000003
1511415115267010812624247302412251121231001000000000001000000000000000000000000000003
151151511626072432325876601702512141282001000010000000000000000000000000000000000003
1511615117260312119633195618249221911325001000010000000000000000000000000000000000003
1511715118249213425365117335250220831187001000010000000000000000000000000000000000003
1511815119248716728218101242229237119932001000010000000000000000000000000000000000003
151191512024751973431978270189244164914001001000000000000000000000000000000000000003